Demographic and Clinical Characteristics of Chronic Myeloid Leukemia Patients: A Study on Confined Populations of Southern India
CC BY-NC-ND 4.0 ? Indian J Med Paediatr Oncol 2019; 40(S 01): S70-S76
DOI: DOI: 10.4103/ijmpo.ijmpo_141_17
Abstract
Context:?Chronic myeloid leukemia (CML) is one of the most common hematological malignancies in all populations throughout the world. Even though the pathophysiology of CML was well explained in majority of the studies, the incidence of CML was shown to exhibit population diversity, and hence, the demographic factors underlying CML origin remain to be understood. Further, the introduction of tyrosine kinase inhibitors had revolutionized the treatment of CML over the years; however, there is a need for developing tailoring therapy to individual risk since the patient clinical heterogeneity poses a major problem during drug response. Therefore, the study of basic clinical picture may aid in planning treatment strategies for CML patients.?Aim:?The aim of this article is to study the epidemiological and clinical variables associated with the prognosis of CML. Subjects and?Methods:?We have considered the distribution of various demographic and clinical variables among 476 CML patients diagnosed at Nizam?s Institute of Medical Sciences, Hyderabad, Telangana, India. Statistical Analysis Used: All the analyses were performed through SPSS software (version 21.0). Correlation and Cox regression analyses were also performed.?Results:?Apart from the elevated male sex ratio in CML incidence, high frequency of males was observed to be nonresponders to imatinib mesylate (IM). IM response was shown to be dependent on phase of diagnosis, whereas overall survival of CML patients depends on the age at onset and response to IM.?Conclusions:?The study of epidemiology and clinical picture of CML patients may help in planning better treatment strategies at diagnosis to achieve long-term progression-free survival.
Publication History
Article published online:
24 May 2021
? 2019. Indian Society of Medical and Paediatric Oncology. This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial-License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/).
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Abstract
Context:?Chronic myeloid leukemia (CML) is one of the most common hematological malignancies in all populations throughout the world. Even though the pathophysiology of CML was well explained in majority of the studies, the incidence of CML was shown to exhibit population diversity, and hence, the demographic factors underlying CML origin remain to be understood. Further, the introduction of tyrosine kinase inhibitors had revolutionized the treatment of CML over the years; however, there is a need for developing tailoring therapy to individual risk since the patient clinical heterogeneity poses a major problem during drug response. Therefore, the study of basic clinical picture may aid in planning treatment strategies for CML patients.?Aim:?The aim of this article is to study the epidemiological and clinical variables associated with the prognosis of CML. Subjects and?Methods:?We have considered the distribution of various demographic and clinical variables among 476 CML patients diagnosed at Nizam?s Institute of Medical Sciences, Hyderabad, Telangana, India. Statistical Analysis Used: All the analyses were performed through SPSS software (version 21.0). Correlation and Cox regression analyses were also performed.?Results:?Apart from the elevated male sex ratio in CML incidence, high frequency of males was observed to be nonresponders to imatinib mesylate (IM). IM response was shown to be dependent on phase of diagnosis, whereas overall survival of CML patients depends on the age at onset and response to IM.?Conclusions:?The study of epidemiology and clinical picture of CML patients may help in planning better treatment strategies at diagnosis to achieve long-term progression-free survival.
Introduction
Chronic myeloid leukemia (CML) is one of the most commonly diagnosed hematological malignancies among adults worldwide, exhibiting population diversity in incidence among Asian and other populations, and even between subpopulations. In spite of extensive knowledge generated on the molecular basis of CML, the etiopathogenesis of 9:22 translocation still remains obscure. Various epidemiological studies on CML have indicated the role of few environmental factors in conferring increased risk to CML, which was further shown to depend on the genetic susceptibility of individuals and level of environmental interactions. Hence, understanding the etiology of CML is considered very important in elucidating the factors influencing CML origin. At present, major sources available for the information on epidemiology of CML are Mortality Statistics, European Cancer Registries (Swedish Cancer Registry and Saarland Registry in Germany), and Database of Surveillance Epidemiology and End Results program of the United States from National Cancer Institute.[1]
Since the introduction of targeted drugs in 2001, relative survival of CML patients had been shown to increase and mortality rates were found to decrease by the use of tyrosine kinase inhibitors (TKIs).[2] [3] The 5-year survival rate of CML patients had been shown to be doubled over the past two decades after the discovery of TKIs, from 31% in the early 1990s to 63% for patients diagnosed from 2005 to 2011.[4] About 90% of CML patients were reported to be diagnosed in the initial, less severe chronic phase (CP). However, 60%?80% of the patients reported in the final, acute blast crisis (BC) phase were found to be preceded by the intermediate accelerated phase (AP),[5] indicating that phase at diagnosis plays a major role in CML prognosis. Majority of the CML patients are given imatinib mesylate (IM) as the front-line therapy, irrespective of the phase in which they are diagnosed, and IM response is measured at hematological, cytogenetic, and molecular levels based on the differential blood cell counts, cytogenetic analysis, and polymerase chain reaction (PCR) tests, respectively, to monitor the progression of disease on a regular basis. The study of the patient clinical picture is probably one of the better approaches to assessing the progression of CML and overall response to IM.
Subjects and Methods
Study population
Population recruited for the study consisted of CML cases (n?= 476) from different socioeconomic strata (from the states Telangana and Andhra Pradesh) diagnosed at Nizam?s Institute of Medical Sciences, Hyderabad, India (during the period 2004?2012). Epidemiology information was obtained from the patient through a prescribed questionnaire. Only primary Philadelphia chromosome positive CML cases on IM treatment were included, irrespective of the phase of disease and duration of treatment being given to the patient. None of these cases were on any other clinical trials. Complete clinical information of the patient, including follow-up and treatment modalities, was noted from the tumor registry of the hospital with the help of a medical oncologist. In spite of our sincere attempts to follow-up all the recruited cases, few patients failed to report regularly and were lost to follow-up due to unknown reasons, and hence, their information could not be recorded. For the case?control comparison study, 449 age- and sex-matched healthy controls without family history of cancers were recruited from local population by visiting households, offices, blood donation camps, etc. Informed consent was taken from all the subjects included in the study. Patient?s personal information was not revealed in the data.
Statistical analyses
The baseline clinical characteristics of CML patients such as differential cell count, platelet count, percentage of blasts, and spleen size were considered in calculating Sokal, Hasford, and European Treatment and Outcome Study (EUTOS) risk scores,[6] [7] [8] using the online calculator,[9] which helped in estimating the risk of progression of patients at the time of diagnosis by grouping them into low-, intermediate-, and high-risk groups. In general, patients in the low-risk groups are expected to achieve complete cytogenetic response (CCR) to treatment earlier than those in the high-risk group.
Bivariate Pearson?s correlation coefficient test was performed to analyze the strength of relationship between two clinical variables. Cox regression analysis was done to identify the impact of clinical characteristics on the event-free survival (EFS) rate. EFS rate was calculated for CML patients diagnosed in CP, as the duration in months, from the date of initiation of IM to the date of showing any sign of progression. All statistical analyses were performed using the SPSS (version 21.0, IBM, Armonk, New York, US) software.
Results and Discussion
Sex ratio
Even though elevated male frequency among CML cases is the universal observation, the male-to-female ratio (sex ratio) was reported to vary between different geographic areas, also for different countries of the Asian population.[10] In India, CML incidence rates were reported as 0.8?2.2 in males and 0.6?1.6 in females (National Cancer Registry Program, 2005),[11] with a wide variation in sex ratio ranging from 1:0.8 to 3:1 for different areas,[12] indicating male predominance. Our study also revealed elevation in male sex frequency similar to the earlier reports with a sex ratio of 1.88:1 [Table 1]. The male preponderance might be attributed to their genetic constitution, inherent immune differences, hormonal levels, likelihood of occupational exposure to various types of radiation and chemicals, and diet, smoking, and alcoholic habits.[13]
Characteristic |
Controls@ n (%) |
CML cases, n (%) |
Mean age at onset?SD |
Sex ratio |
---|---|---|---|---|
?CML cases: mean age=36.34?12.80; range=7-80; median=35; mode=45, @age and sex matched controls were included in the study. CML ? Chronic myeloid leukemia; SD ? Standard deviation |
||||
Age at onset (years)? |
||||
<20> |
62 (13.8) |
35 (7.4) |
15.00?3.73 |
1.92:1 |
20-40 |
269 (59.9) |
280 (58.8) |
30.74?6.10 |
1.64:1 |
>40 |
118 (26.3) |
161 (33.8) |
50.73?7.50 |
2.43:1 |
Gender |
||||
Male |
293 (65.3) |
311 (65.3) |
36.84?13.05 |
1.88:1 |
Female |
156 (34.7) |
165 (34.7) |
35.41?12.32 |
|
Living area |
||||
Rural |
200 (47.3) |
303 (65.2) |
35.49?12.27 |
2.00:1 |
Urban |
223 (52.7) |
162 (34.80) |
38.35?13.38 |
1.61:1 |
Occupation |
||||
Agricultural |
15 (3.6) |
120 (25.4) |
38.88?11.56 |
2.64:1 |
laborers |
||||
Laborers |
110 (26.1) |
160 (33.9) |
36.94?11.00 |
2.90:1 |
Others |
297 (70.4) |
192 (40.7) |
34.26?14.56 |
1.11:1 |
Diet |
||||
Veg |
79 (18.6) |
31 (7.5) |
41.48?14.26 |
1.58:1 |
Nonveg |
346 (81.4) |
385 (92.5) |
36.13?12.56 |
1.89:1 |
Habits |
||||
Smokers, alcoholics |
72 (17.8) |
112 (28.8) |
41.08?11.34 |
- |
No habits |
332 (82.2) |
277 (71.2) |
34.17?12.51 |
- |
Clinical variable |
n (%) |
Mean age?SD |
Sex ratio |
---|---|---|---|
CML ? Chronic myeloid leukemia; SD ? Standard deviation; EUTOS ? European Treatment and Outcome Study |
|||
Phase of CML (n=463) |
|||
Chronic |
396 (85.5) |
36.61?12.863 |
1.87:1 |
Accelerated |
36 (7.8) |
35.03?13.018 |
1.77:1 |
Blast-Crisis |
31 (6.7) |
35.19?11.429 |
2.88:1 |
Hematologic response (n=341) |
|||
Complete |
224 (65.7) |
35.93?12.150 |
1.60:1 |
Partial |
53 (15.5) |
35.89?12.250 |
2.31:1 |
No response |
64 (18.8) |
38.98?13.368 |
2.37:1 |
Cytogenetic response (n=326) |
|||
Complete |
195 (59.8) |
34.87?12.580 |
1.75:1 |
Partial |
59 (18.1) |
33.97?11.269 |
2.69:1 |
No response |
72 (22.1) |
38.08?11.734 |
1.77:1 |
Molecular response (n=381) |
|||
Responders |
213 (55.9) |
35.23?12.527 |
1.63:1 |
Nonresponders |
168 (44.1) |
35.92?12.341 |
2.17:1 |
Sokal score (n=332) |
|||
Low risk |
59 (17.8) |
29.31?10.729 |
1.95:1 |
Intermediate risk |
120 (36.1) |
36.74?12.469 |
1.67:1 |
High risk |
153 (46.1) |
38.57?13.048 |
1.64:1 |
Hasford score (n=270) |
|||
Low risk |
59 (21.9) |
33.69?8.655 |
1.57:1 |
Intermediate risk |
143 (53.0) |
34.27?11.622 |
1.42:1 |
High risk |
68 (25.2) |
42.03?14.575 |
2.09:1 |
EUTOS score (n=355) |
|||
Low risk |
216 (60.8) |
36.90?12.825 |
2.04:1 |
High risk |
139 (39.2) |
36.03?12.410 |
1.44:1 |
Category of response |
Chronic phase |
Accelerated phase |
Blast crisis |
---|---|---|---|
Hematologic response (%) |
|||
Complete |
211 (72.01) |
8 (38.10) |
5 (19.23) |
Partial |
48 (16.38) |
3 (14.29) |
1 (3.85) |
No response |
34 (11.60) |
10 (47.62) |
20 (76.92) |
Cytogenetic response (%) |
|||
Complete |
182 (65.23) |
10 (47.62) |
3 (11.54) |
Partial |
54 (19.35) |
1 (4.76) |
4 (15.38) |
No response |
43 (15.415) |
10 (47.62) |
19 (73.08) |
Molecular response (%) |
|||
Responders |
194 (58.43) |
10 (47.62) |
4 (19.05) |
Nonresponders |
138 (41.57) |
11 (52.38) |
17 (80.95) |
Survival rates |
Males, n (%) |
Females, n (%) |
Sex ratio |
---|---|---|---|
EFS ? Event-free survival |
|||
EFS |
|||
Primary resistance |
47 (46.08) |
24 (52.17) |
0.88:1 |
Secondary resistance |
55 (53.92) |
22 (47.83) |
1.13:1 |
Overall survival (years) |
|||
?4 |
117 (44.15) |
75 (53.57) |
0.82:1 |
>4 |
148 (55.84) |
65 (46.43) |
1.20:1 |
Event |
|||
Alive |
242 (91.32) |
136 (97.84) |
0.93:1 |
Dead |
23 (8.68) |
3 (2.16) |
4.02:1 |
Correlation coefficient (r)\signiflcance (P) |
Age at onset |
WBC count |
Platelet count |
Sokal score |
Hasford score |
EUTOS score |
EFS |
Overall survival |
---|---|---|---|---|---|---|---|---|
r=Pearson correlation coefficient; P=Significance *<0> |
||||||||
Age at onset |
?0.132** |
?0.110* |
0.113* |
0.235** |
?0.040 |
?0.140* |
?0.093 |
|
WBC count |
0.006 |
0.084 |
0.111* |
0.136* |
0.207* |
?0.060 |
?0.031 |
|
Platelet count |
0.024 |
0.085 |
0.009 |
0.044 |
?0.079 |
0.139 |
0.093 |
|
Sokal score |
0.041 |
0.045 |
0.870 |
0.683** |
0.359** |
?0.081 |
0.082 |
|
Hasford score |
0.000 |
0.026 |
0.479 |
0.000 |
0.548** |
0.026 |
?0.129 |
|
EUTOS score |
0.448 |
0.000 |
0.145 |
0.000 |
0.000 |
?0.041 |
?0.195** |
|
EFS |
0.043 |
0.403 |
0.057 |
0.346 |
0.784 |
0.610 |
0.538** |
|
Overall survival |
0.107 |
0.604 |
0.127 |
0.256 |
0.113 |
0.004 |
0.000 |
Variable |
Categories |
Hazardous risk |
95% CI |
P |
---|---|---|---|---|
# P significant at 0.10; *P significant at 0.05; **P significant at 0.01. CI ? Confidence interval; EUTOS ? European Treatment and Outcome Study |
||||
Age at onset |
20-40 years (n=125) |
1.00 (reference) |
- |
- |
<20 class="i alt">n=17) |
0.58 |
0.32-1.03 |
0.06" |
|
>40 years (n=67) |
1.22 |
0.89-1.68 |
0.21 |
|
Sex of patient |
Males versus females |
1.17 |
0.85-1.60 |
0.34 |
Sokal score |
Low risk (n=25) |
1.00 (reference) |
- |
- |
Intermediate (n=54) |
0.80 |
0.48-1.33 |
0.38 |
|
High risk (n=62) |
1.06 |
0.63-1.76 |
0.83 |
|
Hasford score |
Low risk (n=22) |
1.00 (reference) |
- |
- |
Intermediate (n=65) |
1.15 |
0.70-1.90 |
0.59 |
|
High risk (n=26) |
0.87 |
0.46-1.63 |
0.65 |
|
EUTOS score |
Low risk (n=100) |
1.00 (reference) |
- |
- |
High risk (n=61) |
0.99 |
0.70-1.39 |
0.94 |
|
Hematologic response |
Complete (n=88) |
1.00 (reference) |
- |
- |
Partial (n=40) |
1.05 |
0.71-1.55 |
0.81 |
|
No response (n=48) |
2.10 |
1.37-3.23 |
0.001** |
|
Cytogenetic response |
Complete (n=78) |
1.00 (reference) |
- |
- |
Partial (n=38) |
1.49 |
1.00-2.23 |
0.05" |
|
No response (n=55) |
1.42 |
0.96-2.12 |
0.08" |
|
Molecular response |
Complete/major (n=40) |
1.00 (reference) |
- |
- |
No response (n=152) |
1.09 |
0.75-1.57 |
0.65 |
- Rohrbacher M, Hasford J.?Epidemiology of chronic myeloid leukaemia (CML). Best Pract Res Clin Haematol 2009; 22: 295-302
- Leitner AA, Hehlmann R.?Modern therapy of chronic
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